Testing the Limits of Unified Sequence to Sequence LLM Pretraining on Diverse Table Data Tasks

Understand

Tables stored in databases and tables which are present in web pages and articles account for a large part of semi-structured data that is available on the internet.

• It then becomes pertinent to develop a modeling approach with large language models (LLMs) that can be used to solve diverse table tasks such as semantic parsing, question answering as well as classification problems.
• Traditionally, there existed separate models specialized for each task individually.
• It raises the question of how far can we go to build a unified model that works well on some table tasks without significant degradation on others.